Image sensing devices, such as a charge-coupled device (CCD), are commonly found in such products as digital cameras, scanners, and video cameras. These image sensing devices have a very limited dynamic range when compared to traditional negative film products. A image sensing device has a dynamic range of about five stops.
In addition, oftentimes the scene has a very wide dynamic range as a result of multiple illuminants (e.g. frontlit and backlit portions of a scene). In the embodiment of a wide dynamic range scene, choosing an appropriate exposure for the subject often necessitates clipping data in another part of the image. Thus, the inferior dynamic range of an image sensing device relative to silver halide media results in lower quality for images obtained by an image sensing device. Therefore some portions of the image can be over-exposed or under-exposed.
High Dynamic Range (HDR) imaging methods provide higher dynamic range image as compared to the single image capture using conventional camera. HDR imaging has become one of the inherent features on handheld cameras and photo-editing tools. This method of obtaining an image with increased dynamic range is by capturing multiple still images of the same resolution at different exposures, and combining the images into a single output image having increased dynamic range. This approach often uses a separate capture mode and processing path in a digital camera.
Additionally, the temporal proximity of multiple captures is limited by the rate at which the images can be read out from the image sensor. Greater temporal disparity among captures increases the likelihood of motion existing among the captures, whether camera motion related to hand jitter, or scene motion resulting from objects moving within the scene. Motion increases the difficulty in merging multiple images into a single output image.
Additionally, the HDR image generation from multiple exposed images provides increased shadow, middle tone and highlight detail which might not be optimal to the expectation of the user.
Additionally, this single output image, called radiance map, uses more than 8-bit per pixel/channel and cannot be displayed on the Liquid Crystal Display (LCD) or Light Emitting Diode (LED) displays found in current devices and hence have to be tone mapped to 8-bit representation, called Low Dynamic Range (LDR) image. The operator used for this mapping, called Tone mapping operator, maps the radiance map into a low dynamic range image. As a result of this process, some of the regions with comparatively lesser contrast might be represented using lesser colors than rest of the image. Therefore the user might use enhancement of the dynamic range of these regions without affecting the rest of the image. There exist some methods in art for enhancing overall dynamic range of the image.
The generation of HDR image uses one to estimate the camera response function (CRF) and to know the exposure settings. For such methods, dynamic scenes pose a challenge as the moving objects produce artifacts called ‘ghosts’ in the final image. For a dynamic scene, one has to perform additional operations to remove the ghosts introduced due to moving objects in the scene. This process, known as de-ghosting, can be performed by replacing the pixel intensities of the motion regions from one or more of the multi-exposure images without any local motion. De-ghosting algorithms are used to reduce this artifact but, due to the exposure difference in the image capture, the de-ghosting algorithm may not detect or wrongly detect ghosts, hence degrading the HDR image quality.